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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...8 Hits 1 – 20 of 156 1 A Self-Paced Reading Study on Processing Constructions with Different Degrees of Compositionality Rambelli, Giulia; Lenci, Alessandro; Blache, Philippe In: The 35th Annual Conference on Human Sentence Processing ; https://hal.archives-ouvertes.fr/hal-03620795 ; The 35th Annual Conference on Human Sentence Processing, Mar 2022, UC Santa Cruz, United States (2022) BASE Show details 2 Probing for the Usage of Grammatical Number ... Lasri, Karim; Pimentel, Tiago; Lenci, Alessandro. - : arXiv, 2022 BASE Show details 3 Does BERT really agree ? Fine-grained Analysis of Lexical Dependence on a Syntactic Task ... Lasri, Karim; Lenci, Alessandro; Poibeau, Thierry. - : arXiv, 2022 BASE Show details 4 Not all arguments are processed equally: a distributional model of argument complexity [<Journal>] Chersoni, Emmanuele [Verfasser]; Santus, Enrico [Verfasser]; Lenci, Alessandro [Verfasser]. DNB Subject Category Language Show details 5 Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge Pedinotti, Paolo; Rambelli, Giulia; Chersoni, Emmanuele... In: Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; https://hal.archives-ouvertes.fr/hal-03312774 ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, Aug 2021, Online, France. pp.1-11, &#x27E8;10.18653/v1/2021.starsem-1.1&#x27E9; (2021) BASE Show details 6 Not all arguments are processed equally: a distributional model of argument complexity Chersoni, Emmanuele; Santus, Enrico; Lenci, Alessandro... In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-03533181 ; Language Resources and Evaluation, Springer Verlag, 2021, 55 (4), pp.873-900. &#x27E8;10.1007/s10579-021-09533-9&#x27E9; (2021) BASE Show details 7 Universal Dependencies 2.9 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 8 Universal Dependencies 2.8.1 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 9 Universal Dependencies 2.8 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 10 Not all arguments are processed equally: a distributional model of argument complexity Chersoni, Emmanuele; Santus, Enrico; Lenci, Alessandro... In: Springer Netherlands (2021) BASE Show details 11 Decoding Word Embeddings with Brain-Based Semantic Features ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chersoni, Emmanuele; Huang, Chu-ren. - : Underline Science Inc., 2021 BASE Show details 12 Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Blache, Philippe; Chersoni, Emmanuele. - : Underline Science Inc., 2021 BASE Show details 13 A comparative evaluation and analysis of three generations of Distributional Semantic Models ... Lenci, Alessandro; Sahlgren, Magnus; Jeuniaux, Patrick. - : arXiv, 2021 BASE Show details 14 Constructional associations trump lexical associations in processing valency coercion Busso, Lucia; Perek, Florent; Lenci, Alessandro. - 2021 BASE Show details 15 Common-Sense and Common-Knowledge. How much do Neural Language Models know about the world? ROCCHIETTI, GUIDO In: http://etd.adm.unipi.it/theses/available/etd-03122021-000321/ (2021) BASE Show details 16 I neologismi nelle edizioni del 2010 e del 2021 del dizionario "Zingarelli della lingua italiana" BERNI, MATTEO In: http://etd.adm.unipi.it/theses/available/etd-05102021-214231/ (2021) BASE Show details 17 Large-scale Cross-lingual Word Sense Disambiguation using Parallel Corpora PETROLITO, TOMMASO In: http://etd.adm.unipi.it/theses/available/etd-09112021-110903/ (2021) BASE Show details 18 Probing the linguistic knowledge of word embeddings: A case study on colexification BERTOLDO, SARA In: http://etd.adm.unipi.it/theses/available/etd-06212021-172428/ (2021) BASE Show details 19 "Love is an open door but not a table". Come uomini e macchine 'comprendono' le metafore lessicalizzate e creative. DI PALMA, ELIANA In: http://etd.adm.unipi.it/theses/available/etd-03242021-214055/ (2021) Abstract: Metaphor is a widespread linguistic and cognitive phenomenon. Many studies were carried out to investigate how humans understand and produce metaphors. A key aspect of the phenomenon is the difference between frozen and creative metaphors. It was shown that humans interpretate in a different way conventional metaphors and novel metaphors and that humans are sensible to this difference. Our study confirms that result. Furthermore, metaphors, especially creative ones, are difficult to model computationally. Recent progress has been made in metaphor identification, also thanks to the contextualized embeddings from models like BERT. To test what BERT, RoBERTa and GPT2 know about metaphors, we challenge them with a new dataset of conventional and creative metaphors accompanied by various types of human judgments. We find that the models can "recognize" metaphors and shows interesting abilities like that of predicting creative metaphors. At the same time, we show that the models still struggle in "interpreting" metaphorical language, even if it outperforms traditional static vectors. Our findings confirm previous claims about the abilities and limitations of the models. Furthermore, they show that RoBERTa has better performance than BERT and GPT2 in the first experiment and that BERT large is almost good in "interpreting" metaphors in the upper-intermediate layers as suggested by the results of the second experiment. Finally, the models seem to show some similarities with humans, but still miss a significant part of human intuitions about the meaning of metaphors. Keyword: FILOLOGIA; LETTERATURA E LINGUISTICA URL: http://etd.adm.unipi.it/theses/available/etd-03242021-214055/ BASE Hide details 20 Le interpretazioni del concetto di composizionalita' delle espressioni idiomatiche nella letteratura psicolinguistica MELI, ANNALISA In: http://etd.adm.unipi.it/theses/available/etd-09132021-151853/ (2021) BASE Show details Page: 1 2 3 4 5...8

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